Qubit efficient quantum optimization and applications to industrial problems

The research will have both fundamental and applied science components. The former concerns the development, and benchmarking of the algorithms developed in classical emulators, cloud quantum computers or directly in collaboration with collaborating experimental teams; the latter will focus on translating the findings into quantum software applications.

Combinatorial binary optimization problems are known to be hard for classical computers. Quantum solutions based on quantum digital, annealing or variational algorithms promise to solve such problems faster and more efficiently. However, the requirements in the number of physical qubits needed to implement these algorithms are still beyond the reach of any near-term quantum processors.

Here you will be working on novel, physics inspired quantum algorithms, allowing for much larger problems to be tackled with near term quantum processors. These will be applied to a range of industrial use cases from optimizing of shipping routes, to financial optimization, aviation and energy management.

We are seeking curious minds with a solid foundation in the physical, engineering or mathematical sciences. Previous exposure to quantum algorithm or programming courses will be a plus but not necessary.

The project will include funded visits to collaborating groups in the Centre for Quantum Technologies Singapore, Greece, as well as leading theoretical and experimental teams in the US, Asia and the EU.

References

• Qubit efficient quantum algorithms for the vehicle routing problem on quantum computers of the NISQ era. See research summary. 

• Exponential Qubit Reduction in Optimization for Financial Transaction Settlement. See research summary.